Authors:Tantikorn Pichpibul Abstract: In the second half of 2020, The International Scientific Journal of Engineering and Technology (ISJET) would be four years old, and it is a pleasure to present the second issue of 2020. This new issue of ISJET highlights multidisciplinary contents, which include six original research articles involving with a work related to an optimization for production planning, a steel tube production planning and scheduling, an effect of gamification on education, a bullwhip effect prediction in a single echelon supply chain, a factors influencing the microstructure and corrosion resistance of austenitic and duplex stainless, and an augmentation for image classification. I would like to take the opportunity to thank all of those who have contributed to our journal. All authors and readersfrom around the world are invited to visit the website https://www.tci-thaijo.org/index.php/isjet/index. This link will grant you submit your research to publish in our journal or will access to electronic versions of all issues of our journal. I look forward to hearing from you. PubDate: 2020-12-24 Issue No:Vol. 4, No. 2 (2020)
Authors:Navee Chiadamrong, Nathridee Suppakitjarak, Chayanan Tangchaisuk Pages: 1 - 12 Abstract: This paper presents a study of a dedicated remanufacturing system using a simulation-based optimization approach. The remanufacturing system performs various rework processes such as inspection, assembly, disassembly, testing, and repair on used-products and transforms them to be as-new products. In this study, the original production line of this dedicated remanufacturing system is shared with multiple products and has a limited space to accommodate arriving used products. Therefore, an appropriate inventory capacity should be set and a proper switching rule should be introduced to set up the production line. Otherwise, excessive line switching time and cost would be incurred. The objective of this study is to sequentially improve and suggest a method to optimize the production planning of this dedicated remanufacturing system under uncertain conditions, i.e., uncontrollable product arrival and stochastic operational time. A case study is used to demonstrate and identify possible solutions, to show the advantages of the proposed approach. This approach can assist in decision making for the planning and management of remanufacturing systems. PubDate: 2020-12-24 Issue No:Vol. 4, No. 2 (2020)
Authors:Chayaporn Maitreesorasuntee, Chawalit Jeenanunta, Jirachai Buddhakulsomsiri, Warut Pannakkong, Rujira Chaysiri, Nakamura Masahiro, Jessada Karnjana Pages: 13 - 19 Abstract: Steel tube manufacturing industry is one of heavy industry that use a lot of labor, large and heavy machineries, intense capital, and high technologies. The production planning and scheduling of steel tube manufacturing is complicated because of a long tool setup time and machine conditions. Moreover, there are half-thousands of different finished goods. In order to produce efficiently and maximize machine utilization, this paper proposes a digital twin of steel tube production process focus on forming process. The digital twin could be used for planning and scheduling to manage complexity of machinery setup, priorities production, fulfil inventory without shortage and to conduct what-if analysis and compares for the scenarios of different schedules. The digital twin provides production model simulating precise production total time, tool setup time, number of products and production deadline. The simulation model is tested with forty-nine products on three identical machines with their tool setup time. It reduces the production planning time of the planning engineer and provides accurate schedule of each product. PubDate: 2020-12-23 Issue No:Vol. 4, No. 2 (2020)
Authors:Phannachet Na Lamphun, Jian Qu, Pornsak Preelakha Pages: 20 - 27 Abstract: It is necessary for traditional offline teaching to be transformed into online teaching to continue education during emergencies. The technology is ready for the transition of teaching from traditional classes to online classes. However, it is difficult to achieve successful online live teaching due to several factors, including distraction, motivation, and self-directed learning of the learner. Therefore, gamification has been selected to apply to online live teaching. By applying the game mechanic including game and reward system, this motivates the learners and increases their participation. The result illustrates that gamification can help increase participation and motivate learners in online teaching compared to in-class teaching. Moreover, by extending the research to apply gamification to pure online lives teaching, the result shows that it is guaranteed to help motivate the learners to attend the classes, participate in activities, and make discussions, thus increasing the understanding of course materials reflected by the activities and quiz scores. This fact shows that gamification is necessary for online live teaching which can help support motivation and increase participation in online live class learning. PubDate: 2020-12-23 Issue No:Vol. 4, No. 2 (2020)
Authors:Navee Chiadamrong, Nont Sarnrak, Nathridee Suppakitjarak Pages: 28 - 40 Abstract: One of the main problems in supply chain systems is the bullwhip effect that can generate a huge cost for the companies in a chain.In this study, the factors and their impacts that can cause the bullwhip effect (order variance and net stock amplification) are investigated by using a simulation-based optimization approach. The proposed meta-prediction model is built using regression analysis, to predict the Total Stage Variance Ratio (TSVR) of the system. A single-echelon supply chain with uncertain customer demand operating under the periodic-review reorder cycle policy is studied. The parameters of the smoothing inventory replenishment and forecasting methods are required to search for their optimality in reducing the TSVR by OptQuest, an optimization tool in ARENA simulation software. Our results can assist decision makers in the management of a supply chain, to realize, benchmark, and reduce the TSVR under an uncertain environment. PubDate: 2020-12-23 Issue No:Vol. 4, No. 2 (2020)
Authors:John T. H. Pearce , Paritud Bhandhubanyong Pages: 41 - 51 Abstract: The demand for Austenitic and Duplex Stainless Steel Castings has increased with investment in the petrochemical industry, transportation infrastructure and electric vehicle production in Thailand. To achieve high quality casting of these two grades, alloying elements melt quality, pre- and post—treatment of castings play an important role in quality level determination. These important factors are discussed along with guidelines for good manufacturing practices to achieve the required microstructures and high quality castings from the domestic foundry sector in Thailand. PubDate: 2020-12-23 Issue No:Vol. 4, No. 2 (2020)
Authors:Thitiporn Khantong, Parinya Sanguansat Pages: 52 - 60 Abstract: For image classification to be more accurate, image files with high resolution were to be put up for test. Practically, the set of images obtained for classification might be low resolution files. In this case, it was more difficult to do image classification. The result was that the accuracy rate was low. It was unable to be applied for work. We studied to find a solution to fix this problem. The answer to the problem was to do data augmentation which was consisted of Affine Transformation and Super Resolution. Affine Transformation are all linear transformations which can be represented by a matrix and combined into a single overall including rotation, scaling, translation and shearing where all points in an object are transformed in the same way. Immage Super Resolution is made to increase the resolution and quality of image. This method has been shown that it outperformed the basic interpolation method. In this research, we studied whether Super Resolution is able to enhance the discriminative features of the image and such transformed image is more amenable to classification process. It can be seen that the methods applied were useful to accurately and precisely identify low resolution image files. Besides, we adopted a transfer learning method which was designed and developed for the task. It has been reused as the starting point for a model on the second task which could help us classify the type of image more accurately and precisely. PubDate: 2020-12-23 Issue No:Vol. 4, No. 2 (2020)
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